Offer summary

Qualifications:

5+ years of experience in Data Science with a focus on analytics-driven product development., Proven experience in building and deploying recommendation engines and analytical tools., Strong proficiency in Python and machine learning libraries like TensorFlow or PyTorch., Expertise in predictive modeling and strong SQL skills for working with large datasets..

Key responsibilities:

Develop and deploy recommendation systems to provide data-driven advice.

Build analytics-backed software and dashboards for customer insights and performance metrics.

Collaborate with product and engineering teams to integrate machine learning outputs into user-facing tools.

Lead the design of A/B testing frameworks to validate new data-driven features.

Job description

About Cashea

Cashea is a Buy Now Pay Later (BNPL) fintech company focused on providing credit access to Venezuelan people, democratizing financial inclusion through technology. We work in cross-functional squads, each with dedicated technical leads for frontend and backend development.

About the Role

Shape the future by building intelligent recommendation engines, insightful analytics dashboards, and powerful predictive models that drive strategic decisions and enhance user experiences. You'll collaborate with cross-functional teams to seamlessly integrate your data-driven innovations, lead impactful experiments, and champion the ethical application of AI, all while mentoring and elevating your fellow data professionals.

You Will:

Develop and deploy recommendation systems that provide data-driven advice and optimal courses of action.
Build analytics-backed software and dashboards to access insights on customer behavior, transaction trends, and performance metrics.
Create predictive models for risk assessment, customer segmentation, and merchant success analytics.
Collaborate with product and engineering teams to ensure machine learning outputs are effectively integrated into user-facing tools.
Lead the design of experimentation frameworks (A/B tests) for validating new data-driven features or strategies.
Automate repetitive analytical tasks to improve team efficiency.
Ensure the fairness, transparency, and ethical use of AI in all analytical products.
Provide mentorship to junior data scientists and analysts on advanced modeling techniques and best practices.

You Have:

5+ years of experience in Data Science, with exposure to analytics-driven product development.
Proven experience in building and deploying recommendation engines, dashboards, or other user-facing analytical tools.
Strong proficiency in Python and machine learning libraries such as MLlib, scikit-learn, TensorFlow, or PyTorch.
Experience with MLOps tools (e.g., Vertex AI, Kubeflow) for deploying models at scale.
Expertise in predictive modeling, cohort analysis, and customer segmentation.
Strong SQL skills and experience working with large-scale datasets in cloud environments like GCP.
Ability to communicate complex data insights to technical and non-technical stakeholders effectively.
Familiarity with A/B testing frameworks and experimentation.
Fluent English.